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Microsoft Fabric > Implementing Analytics Solutions - 1 > Flashcards

Implementing Analytics Solutions - 1 Flashcards

DP 600 - Certification

1
Q

What type of Fabric license should you recommend for supporting 10 Microsoft Power BI report authors and 600 report consumers using Dataflow Gen2, while minimizing costs?

A

F64

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2
Q

Imagine you are planning a Fabric analytics solution for 2,000 Power BI consumers without an individual Power BI Pro license, 32 Power BI modelers with an individual Power BI Pro license, and 16 data scientists. What Fabric capacity SKU would minimize costs?

A

F64

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3
Q

True or False: Adding a user to the workspace as a viewer and sharing the lakehouse with them while selecting ‘Read all SQL Endpoint data’ will grant them read-only access without allowing Spark queries.

A

False

The correct approach is to share the lakehouse with User1 directly and select ‘Read all SQL Endpoint data.

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4
Q

Fill-in-the-Blank: To collaborate on a Power BI model with another modeler, you should save your work as a Power BI Project (PBIP) and initialize a ___________

A

Git repository with version control

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5
Q

Which of the following should be used to reduce the size of query requests sent to an Azure SQL database when refreshing a semantic model in a Fabric deployment pipeline?

A

Deployment parameter rule

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6
Q

Why is it recommended to use cross-database querying between Warehouse1 and Warehouse2 to combine sales data from Warehouse2 with HR data from Warehouse1?

A

It minimizes development effort and data movement by allowing direct queries across databases without the need to duplicate data.

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7
Q

You have a Microsoft Power BI report that contains three DAX measures named Sales, Units, and Customers. You need to apply logic-based DAX formatting to the Sales measure. How should you apply the logic?

A

Use dynamic measure formatting

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8
Q

What is the correct method to ingest a large Azure SQL Database table containing over 500 million records into a Fabric lakehouse?

A

Use a pipeline with the Copy data activity

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9
Q

Which join type should you use in Power Query Merge to ensure that all rows in the Employee table are preserved and include any matching rows from the Contract table?

A

Left outer

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10
Q

You have a Fabric warehouse that contains customer status information. You need to implement a dimensional model that supports point-in-time analysis. Which type of dimension should you use for dimCustomer?

A

Type 2 slowly changing dimension (SCD)

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11
Q

What is the recommended approach to enable workspace management and data security in Microsoft Fabric?

A

Implement workspace and item-level access controls, use sensitivity labels, and configure Fabric-enabled workspace settings.

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12
Q

How can you optimize performance when loading data into a Fabric lakehouse?

A

Implement file partitioning and optimize Delta table file sizes using v-order and optimized writes.

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13
Q

What should you do to minimize development effort when querying data across multiple warehouses in Fabric?

A

Use cross-database querying to combine data without duplicating it.

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14
Q

True or False: You can use a Power BI Project (.pbip) file to integrate version control directly in Power BI Desktop.

A

TRUE

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15
Q

Fill-in-the-Blank: To maintain point-in-time analysis in a data warehouse, implement a ____________ dimension.

A

Type 2 slowly changing

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16
Q

What is the key benefit of using DAX Studio when working with large datasets in Fabric?

A

It improves DAX performance and allows detailed analysis of queries.

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17
Q

Which Fabric component should you use to copy data from Azure SQL Database to a lakehouse with minimal manual intervention?

A

Data pipeline with Copy data activity

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18
Q

How can you implement dynamic security in a Power BI report in Fabric?

A

Use dynamic row-level security (RLS) and object-level security (OLS).

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19
Q

When should you choose Direct Lake mode over other storage modes in Fabric?

A

When low-latency access to lakehouse data is required for real-time analytics.

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20
Q

What is the purpose of using deployment parameter rules in a Fabric deployment pipeline?

A

To reduce query size and optimize performance during data refreshes.

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21
Q

How can you optimize SQL query performance in a Fabric warehouse?

A

By resolving data loading bottlenecks and optimizing SQL query structures.

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22
Q

What is the correct method to add predictive analytics capabilities to a Fabric Power BI report?

A

Integrate prescriptive and predictive analytics into visuals using DAX and Python.

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23
Q

Which Fabric feature allows for managing changes across multiple workspaces and their assets?

A

Implementing version control for workspaces and assets.

24
Q

How do you manage large format datasets in Fabric to optimize performance?

A

Implement incremental refresh and use composite models with aggregations.

25
Q

True or False: Tabular Editor 2 is used to optimize semantic models in Fabric by creating and managing DAX calculations.

A

TRUE

26
Q

Which analytics solution component in Fabric allows for the direct ingestion of large datasets using data flows?

A

Dataflows with Fast Copy

27
Q

How should you approach data cleansing in a Fabric lakehouse to ensure accuracy?

A

Implement a data cleansing process using SQL or PySpark.

28
Q

What is the recommended practice for implementing slowly changing dimensions in a Fabric warehouse?

A

Use Type 1 for overwriting data and Type 2 for maintaining historical data.

29
Q

How do you achieve real-time data analytics in a Fabric solution?

A

Use Direct Lake mode with a low-latency data access approach.

30
Q

What strategy should you use to reduce data movement and duplication when combining datasets from different sources in Fabric?

A

Use cross-database querying.

31
Q

What is the primary purpose of using bridge tables in a Fabric semantic model?

A

To handle many-to-many relationships and maintain data integrity.

32
Q

How can you enhance a Power BI report’s performance in Fabric when dealing with large datasets?

A

Implement incremental refresh and use composite models.

33
Q

What method is best suited for denormalizing data in a Fabric lakehouse?

A

Using SQL transformations or PySpark scripts.

34
Q

How should you schedule data pipelines in Fabric to ensure consistent data availability?

A

Use scheduled triggers in data pipelines and coordinate with upstream dataflows.

35
Q

Which Fabric tool is essential for profiling data before implementing transformations?

A

The visual query editor or SQL queries in Fabric.

36
Q

What are the advantages of using a star schema in a Fabric lakehouse?

A

It simplifies query performance and supports analytic workloads.

37
Q

What should you use to implement bridge tables in a Fabric semantic model for complex relationships?

A

Many-to-many relationships and bridge tables.

38
Q

True or False: Object-level security (OLS) can be used in Fabric to restrict access to specific measures in a Power BI model.

A

TRUE

39
Q

How can you optimize the performance of a Fabric dataflow when dealing with large volumes of data?

A

Use partitioning and optimize dataflows with Fast Copy.

40
Q

What is the purpose of using calculation groups in a Fabric semantic model?

A

To simplify and standardize complex calculations across the model.

41
Q

How should you design a composite model in Fabric to optimize performance?

A

Incorporate aggregations and use Direct Lake or import modes appropriately.

42
Q

What is the key advantage of using incremental refresh in a large Fabric dataset?

A

It reduces processing time by only refreshing new or changed data.

43
Q

Which method should you use to resolve duplicate data issues in a Fabric lakehouse?

A

SQL deduplication techniques or data cleansing processes.

44
Q

How do you ensure security and governance in a Fabric workspace?

A

Implement sensitivity labels, manage access controls, and configure workspace settings.

45
Q

What is the primary benefit of using PySpark in a Fabric lakehouse?

A

To perform large-scale data transformations and advanced analytics.

46
Q

What feature should you use to optimize DAX calculations in a Fabric semantic model?

A

Use DAX Studio and Tabular Editor for performance tuning.

47
Q

How can you perform impact analysis of downstream dependencies in a Fabric deployment?

A

By tracking dependencies in lakehouses, data warehouses, and dataflows.

48
Q

What type of Fabric license should you recommend for supporting 10 Microsoft Power BI report authors and 600 report consumers using Dataflow Gen2, while minimizing costs?

A

F64

49
Q

Imagine you are planning a Fabric analytics solution for 2,000 Power BI consumers without an individual Power BI Pro license, 32 Power BI modelers with an individual Power BI Pro license, and 16 data scientists. What Fabric capacity SKU would minimize costs?

A

F64

50
Q

True or False: Adding a user to the workspace as a viewer and sharing the lakehouse with them while selecting ‘Read all SQL Endpoint data’ will grant them read-only access without allowing Spark queries.

A

False

The correct approach is to share the lakehouse with User1 directly and select ‘Read all SQL Endpoint data.

51
Q

Fill-in-the-Blank: To collaborate on a Power BI model with another modeler, you should save your work as a Power BI Project (PBIP) and initialize a ___________

A

Git repository with version control

52
Q

Which of the following should be used to reduce the size of query requests sent to an Azure SQL database when refreshing a semantic model in a Fabric deployment pipeline?

A

Deployment parameter rule

53
Q

Why is it recommended to use cross-database querying between Warehouse1 and Warehouse2 to combine sales data from Warehouse2 with HR data from Warehouse1?

A

It minimizes development effort and data movement by allowing direct queries across databases without the need to duplicate data.

54
Q

You have a Microsoft Power BI report that contains three DAX measures named Sales, Units, and Customers. You need to apply logic-based DAX formatting to the Sales measure. How should you apply the logic?

A

Use dynamic measure formatting

55
Q

What is the correct method to ingest a large Azure SQL Database table containing over 500 million records into a Fabric lakehouse?

A

Use a pipeline with the Copy data activity

56
Q

Which join type should you use in Power Query Merge to ensure that all rows in the Employee table are preserved and include any matching rows from the Contract table?

A

Left outer

57
Q

You have a Fabric warehouse that contains customer status information. You need to implement a dimensional model that supports point-in-time analysis. Which type of dimension should you use for dimCustomer?

A

Type 2 slowly changing dimension (SCD)

Microsoft Fabric (1 decks)

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